An energy-saving and wind-disturbance-resistant flight control method for drones based on wind energy utilization

Abstract

The present invention relates to the technical field of unmanned aerial vehicle (UAV) flight control, and relates to an energy-saving and wind-disturbance-resistant flight control method for UAVs based on wind energy utilization. First, by partially modeling the wind field, some dynamic characteristics of the environmental wind field are incorporated into the UAV dynamics model to achieve a quantitative analysis of the impact of the wind field on flight. Secondly, a sliding mode control strategy is adopted to improve the disturbance resistance ability of the UAV in the wind field. At the same time, a disturbance observer is designed to estimate the disturbance characteristics of the wind field in real time, and a wind energy utilization judgment condition is proposed based on mechanical analysis to dynamically adjust the UAV control strategy. By combining wind field modeling, a disturbance observer, and a sliding mode control strategy, and analyzing the impact of wind energy on the flight of a quadrotor UAV, the present invention realizes the effective utilization of wind field energy to improve flight energy efficiency and enhance the wind-disturbance resistance ability. This method can be widely applied to tasks such as UAV inspection, environmental monitoring, and emergency rescue, and is particularly suitable for flight scenarios with complex wind fields and limited energy supply.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) flight control, and more specifically, to an energy-saving and wind-disturbance-resistant flight control method for UAVs based on wind energy utilization. Background Art

[0002] Quadrotor UAVs are widely used in environmental monitoring, logistics transportation, disaster relief, inspection and other fields due to their advantages such as simple structure, strong mobility and flexible control. However, since they rely on rotors to generate lift and control torque, they are prone to be disturbed by the external wind field during actual flight. Especially in complex environments such as low-altitude wind shear and gusts, problems such as unstable attitude, trajectory deviation and increased energy consumption are likely to occur. The current UAV flight control systems mainly focus on improving the wind-disturbance resistance ability, but there is less research on wind energy utilization, and the potential assistance of environmental wind energy to UAV flight has not been effectively explored. Therefore, how to reasonably utilize wind energy to achieve energy-saving flight of UAVs while resisting wind disturbances is still an urgent problem to be solved.

[0003] Currently, UAV wind-disturbance-resistant control mainly relies on methods such as robust control, adaptive control and predictive control. Among them, robust control improves the stability of UAVs in the wind field by enhancing the anti-interference ability of the system, but it is usually relatively conservative and difficult to balance energy efficiency; adaptive control can adjust the control strategy according to the changes in the wind field, but has high requirements for real-time performance and is easily affected by sensor noise; predictive control relies on the estimation of the future wind field to optimize the control input, but in complex wind fields, it is difficult to guarantee the prediction accuracy and the calculation cost is also high. In addition, the existing control methods mainly focus on weakening the influence of wind field disturbances on UAVs, and rarely consider how to reasonably utilize wind field energy to assist flight and reduce energy consumption. This makes current UAVs still face large energy consumption and endurance bottlenecks when flying in complex environments. Summary of the Invention

[0004] The purpose of the present invention is to provide an energy-saving and wind-disturbance-resistant flight control method for UAVs based on wind energy utilization to solve the problems of high energy consumption, limited wind-disturbance resistance ability and inability to effectively utilize wind energy of existing quadrotor UAVs when flying in a wind field environment as mentioned in the above background art.

[0005] To achieve the above purpose, the present invention provides an energy-saving and wind-disturbance-resistant flight control method for UAVs based on wind energy utilization, including the following steps:

[0006] S1. Establish a wind field dynamics model applicable to quadrotor UAVs and incorporate it into the UAV dynamics equation to quantitatively analyze the influence of the wind field on UAV flight;

[0007] S2. Design a sliding mode controller to control the UAV flying under wind field disturbances through a sliding mode control strategy;

[0008] S3. Construct a disturbance observer to estimate the remaining wind disturbance and lumped disturbance in real time, and propose a wind energy utilization judgment condition in combination with the analysis of the mechanical characteristics of the wind field;

[0009] S4. When the wind energy utilization condition is met, adjust the UAV control strategy and use the wind field energy to partially replace the UAV's own power demand.

[0010] As a further improvement of this technical solution, the wind field dynamics model in step S1 includes the integration of the following components:

[0011] Mean wind component , obtained by measuring the ambient reference wind speed;

[0012] Wind shear component , calculated according to the flight altitude and the wind shear formula where is the measurement height of the mean wind component, is the wind shear index.

[0013] As a further improvement of this technical solution, the design of the sliding mode controller in step S2 includes:

[0014] Adopt the terminal sliding mode function , where , , are the designed parameters;

[0015] Ensure the reachability of the sliding mode surface through the control quantity.

[0016] As a further improvement of this technical solution, the disturbance observer in step S3 is designed as:

[0017]

[0018] As a further improvement of this technical solution, the wind energy utilization judgment conditions in step S4 include:

[0019] Wind field disturbance utilization condition ;

[0020] Remaining disturbance utilization condition ;

[0021] When = 0 or = 0, retain the corresponding disturbance to assist flight.

[0022] As a further improvement of this technical solution, the dynamic adjustment of the control strategy is achieved by updating the control quantity:

[0023]

[0024] Among them, Take values according to the judgment conditions of step S4.

[0025] As a further improvement of this technical solution, when realizing energy-saving flight by using the disturbance in the operating environment in step S4, the following steps are required to further judge the effectiveness of energy-saving flight:

[0026] Select the Lyapunov function as , combined with the sliding mode function and the control algorithm For Taking the derivative gives:

[0027]

[0028] When the disturbance characteristics meet the utilization conditions, and Take 0 to retain the influence of the disturbance, and then improve The speed of tending to 0 to achieve energy-saving and disturbance-resistant flight.

[0029] Compared with the prior art, the beneficial effects of the present invention are:

[0030] 1. Improve the anti-wind disturbance ability: The sliding mode control strategy enhances the robustness of the system to wind field disturbances and improves the stability of the UAV in a strong wind environment.

[0031] 2. Reduce flight energy consumption: Through the wind energy utilization strategy, reduce the energy consumption of the UAV's own power system and improve the endurance.

[0032] 3. Enhance environmental adaptability: Use wind field modeling and disturbance observers to estimate real-time wind field disturbances, enabling the UAV to adapt to different wind field conditions and improving flight flexibility and reliability.

[0033] 4. Optimize the flight control strategy: Combine anti-wind disturbance control and wind energy utilization to achieve intelligent control of the UAV in the wind field and improve the execution efficiency of flight tasks. Description of the Drawings

[0034] Figure 1 It is the overall control block diagram of the UAV energy-saving anti-wind disturbance flight control method based on wind energy utilization of the present invention.

[0035] Figure 2 It is the modeling flowchart of the wind disturbance part based on the UAV operating environment in an embodiment of the present invention.

[0036] Figure 3 It is the anti-disturbance control algorithm flowchart of a quadrotor UAV based on sliding mode control in an embodiment of the present invention.

[0037] Figure 4 This is a flowchart of an energy-saving and disturbance-resistant flight method for a quadrotor UAV based on wind disturbance analysis in an embodiment of the present invention. Specific embodiments

[0038] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] The present invention provides an energy-saving and wind-disturbance-resistant flight control method for an unmanned aerial vehicle based on wind energy utilization, including the following steps:

[0040] S1. Establish a wind field dynamics model applicable to a quadrotor UAV, integrate it into the UAV dynamics equation, and quantitatively analyze the influence of the wind field on the UAV flight;

[0041] S2. Design a sliding mode controller to control the UAV flying under wind field disturbances through a sliding mode control strategy;

[0042] S3. Construct a disturbance observer to estimate the remaining wind disturbance and lumped disturbance in real time, and combine the analysis of the mechanical characteristics of the wind field to propose a wind energy utilization judgment condition;

[0043] S4. When the wind energy utilization condition is met, adjust the UAV control strategy to use the wind field energy to partially replace the UAV's own power demand.

[0044] Embodiment 1:

[0045] As Figure 1 shown, the present invention provides an energy-saving and disturbance-resistant control method for a quadrotor UAV. The method includes a user layer 10, an algorithm layer 20, and a device layer 30. The functions of each layer are as follows:

[0046] User layer 10: The user observes the operating environment of the quadrotor UAV in real time and sends control instructions through the control device 101. The instructions include information such as the desired position or attitude. The function of the control device is limited to sending the desired state instructions, without restricting the specific type of the control device.

[0047] Algorithm layer 20: This layer includes a state error generation module 201, a disturbance-resistant algorithm module 202, and an energy-saving algorithm module 203. Among them, the disturbance-resistant algorithm and the energy-saving algorithm are designed based on the state error respectively, and finally generate a control algorithm 204. The control algorithm is formed by the synergistic action of the disturbance-resistant algorithm and the energy-saving algorithm to achieve the stable control and energy optimization of the UAV.

[0048] Device layer 30: This layer corresponds to the quadrotor UAV and its operating environment. The wind energy in the environment is analyzed and utilized by the energy-saving algorithm 203 in the algorithm layer 20, so as to achieve energy-saving flight of the UAV while ensuring flight stability.

[0049] Embodiment 2:

[0050] As Figure 2 shown, to achieve energy-saving flight of the quadrotor UAV, the present invention constructs a state error model of the UAV and a partial wind field model of the operating environment. This model can partially reflect the wind field characteristics in the environment where the UAV is located and provide wind field disturbance information for the control algorithm. The specific steps are as follows:

[0051] Step S2-1: After the control instruction is issued in the user layer, the expected position given by the expected state generation instruction is obtained , which are the expected positions of the UAV on the three axes in the space coordinate system respectively. This position is the given position that the quadrotor UAV needs to track; the current position of the quadrotor UAV obtained by GPS is set as , which are the actual positions of the UAV on the three axes in the space coordinate system respectively. The final state error is set as , which are the position errors of the UAV on the three axes in the space coordinate system respectively, and are obtained by subtracting the expected position from the current position of the UAV.

[0052] Step S2-2: In the modeling of the wind field, the wind field is split into the mean wind component , which are the mean wind components on the three axes in the space coordinate system respectively, and the wind shear component , which are the wind shear wind components on the three axes in the space coordinate system respectively: The mean wind component is the reference value of the wind speed in the environment and is the average wind speed at a certain height; the wind shear component is the increase in wind speed as the flight height of the UAV increases. According to the flight height of the UAV, the wind shear component of the UAV is obtained by the wind shear formula, and the wind shear formula is:

[0053]

[0054] where is the measurement height of the mean wind component, is the wind shear index;

[0055] Step S2-3: Integrate the average wind component and the wind shear component to obtain a part of the wind disturbance in the UAV operating environment , construct the magnitude and direction of the wind disturbing force of the UAV according to the wind force formula, and the wind force formula is:

[0056]

[0057] where , are respectively the magnitudes of the wind force effects on the UAV on the three axes in the space coordinate system, is the wind resistance coefficient of the UAV, is the air density, is the frontal area of the UAV, is the differential speed between the UAV and the wind speed, is used to judge whether the UAV speed direction is consistent with the wind speed direction, indicates that the speed directions are consistent, indicates that the speed directions are inconsistent.

[0058] Embodiment 3:

[0059] To implement the control algorithm for energy-saving flight in the UAV operating environment, it is first necessary to ensure the stability of the UAV, that is, to have the ability to resist disturbances. Traditional control algorithms are difficult to balance between anti-disturbance performance and energy-saving performance, and usually need to trade off between control accuracy and energy consumption.

[0060] The present invention first adopts a sliding mode control algorithm to achieve anti-disturbance control of the UAV, and on this basis, an energy-saving algorithm is introduced to enable the UAV to more efficiently utilize wind energy and reduce energy consumption. Therefore, the present invention adopts a control strategy combining a sliding mode control algorithm and an energy-saving algorithm to improve the wind disturbance resistance ability of the UAV and achieve energy-saving flight.

[0061] The specific control process of the UAV sliding mode control algorithm is as Figure 3 shown, and the specific steps are as follows:

[0062] Step S3-1: First, establish the UAV position controlled mathematical model in combination with the wind field model as:

[0063]

[0064] where is the mass of the UAV, are respectively the accelerations on the three axes, are respectively the control quantities on the three axes, are respectively the drag coefficients, are respectively the speeds on the three axes, are respectively the wind disturbances on the three axes, They are the remaining lumped disturbances on the three axes respectively. According to the desired state, the controlled model is transformed into an error model. Due to the symmetry of the quadrotor UAV, only the design of the control algorithm on one of the axes is introduced here. In the present invention, the same control method is adopted for each axis, and the error model is:

[0065]

[0066] Where are respectively the velocity error and acceleration error on the axis, and is the desired acceleration on the

[0067] Step S3-2: To achieve more effective tracking on the basis of disturbance rejection, the terminal sliding mode control algorithm is adopted to achieve faster tracking, and the sliding mode function is designed as:

[0068]

[0069] Where , is the designed parameter, , are the position error and velocity error respectively.

[0070] Step S3-3: To ensure the reachability of the sliding mode surface and the disturbance rejection performance of the control algorithm, the control algorithm is designed as:

[0071] ,

[0072] Where, is the mass of the UAV, is the sliding mode function design parameter, is the upper bound of the remaining unknown disturbance is the sign function with respect to ;

[0073] Where ensures the stability of the system.

[0074] Example 4:

[0075] On the basis of realizing disturbance rejection control in step three, the energy-saving flight of the quadrotor UAV is further achieved by combining an energy-saving algorithm. The key to energy-saving flight lies in the accurate estimation of the external environment. Therefore, on the basis of partially modeling the external wind field, it is also necessary to accurately estimate the remaining wind disturbances and the lumped disturbances in the modeling. For this purpose, the present invention designs a disturbance observer for observing and estimating the effects of the remaining wind disturbances and the lumped disturbances. In the stability analysis of sliding mode control, the Lyapunov analysis method is usually adopted, and the same method can also be used in the analysis of energy-saving effects.

[0076] Based on the above analysis, the present invention first further designs a disturbance observer on the basis of the control algorithm in step three, and analyzes the disturbance characteristics respectively based on the observed values and the wind field model to judge whether the disturbance is beneficial to the energy-saving flight of the quadrotor UAV. According to the judgment result, it is decided whether to use the wind disturbance and the remaining lumped disturbances to optimize the energy-saving flight of the UAV. The specific energy-saving flight control process is as Figure 4 shown, and the specific implementation steps are as follows:

[0077] Step S4-1: The mechanical characteristics of the wind field can be directly judged by the positive and negative characteristics of the wind force formula, while the judgment of the characteristics of the remaining disturbances first requires accurate disturbance estimation. In the present invention, the designed disturbance observer is:

[0078]

[0079] where are auxiliary variables respectively, is the observation gain. Based on the designed disturbance observer, the accurate estimation of the remaining wind disturbances and the lumped disturbances in the quadrotor UAV can be realized. Combining the partial wind disturbance information in the wind field model, the detailed characteristics of all disturbances received by the quadrotor UAV can be comprehensively known.

[0080] Step S4-2: After knowing the characteristics of all disturbances, the energy-saving algorithm in the control algorithm can be designed according to the characteristics. The energy-saving algorithm is realized by using the disturbances that are beneficial to the system operation in the disturbances. Therefore, it is necessary to design utilization judgment conditions for the disturbances respectively. First, design the wind disturbance utilization condition in the wind field model:

[0081]

[0082] where the judgment condition is used to ensure that the wind disturbance is retained when the force action characteristic of the wind field disturbance is beneficial to the stability of the system. Subsequently, the characteristics of the disturbances are judged, and the disturbance utilization condition is designed for the characteristics of the observation result as:

[0083]

[0084] where the judgment condition To ensure that when the remaining wind disturbances and the lumped disturbance characteristics in the modeling are beneficial to the stability of the system, the disturbances are retained.

[0085] Step S4-3: Based on the designed disturbance utilization characteristics combined with the control algorithm as Figure 3 shown, update the control algorithm to:

[0086]

[0087] When the characteristics of the disturbance meet the utilization conditions in Step S4-3, and will be eliminated to ensure that the control algorithm does not suppress the disturbances in the operating environment of the quadrotor UAV, thereby realizing the effective utilization of these disturbances. When these disturbances can be utilized, the UAV can utilize part of the energy in the environment to assist in flight, thereby realizing energy-saving flight control.

[0088] Step S4-4: When using the disturbances in the operating environment to achieve energy-saving flight, it is necessary to further judge the effectiveness of the energy-saving flight. In the analysis of the control effect of sliding mode control, the reachability and stability of the system are usually judged by using Lyapunov analysis method. Therefore, the same method is also adopted in the present invention for analysis. Select the Lyapunov function as , combined with the sliding mode function and the control algorithm For Derivation gives:

[0089]

[0090] When the disturbance characteristics meet the utilization conditions, and take 0 to retain the influence of the disturbance, thereby enhancing tends to 0 to achieve energy-saving disturbance rejection flight.

[0091] In summary, through the comprehensive control method of wind field modeling, sliding mode control, disturbance observation and wind energy utilization, the quadrotor UAV of the present invention can fly stably, efficiently and energy-savingly in the wind field environment, is applicable to various application scenarios such as inspection, logistics, emergency rescue, etc., and has broad application prospects and industrial value.

[0092] The basic principles, main features and advantages of the present invention have been shown and described above. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and the descriptions in the specification are only preferred examples of the present invention and are not used to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of the present invention claimed is defined by the appended claims and their equivalents.

Claims

1. A wind energy-saving and wind-disturbance-resistant flight control method for a UAV, characterized in that: The following steps are involved: S1. Establish a wind field dynamics model suitable for quad-rotor UAVs and integrate it into the UAV dynamics equation to quantitatively analyze the impact of wind field on UAV flight; S2. Design a sliding mode controller to control the UAV flying under wind field disturbance through sliding mode control strategy; S3. Construct a disturbance observer to estimate the residual wind disturbance and lumped disturbance in real time, and propose wind energy utilization judgment conditions based on the analysis of wind field mechanical characteristics; S4. When the conditions for wind energy utilization are met, adjust the UAV control strategy and use the wind field energy to partially replace the UAV's own power requirements.

2. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 1 is characterized in that: The wind farm dynamics model in step S1 includes the integration of the following components: Average wind component , obtained by measuring the environmental reference wind speed; Wind shear component , according to the flight altitude and wind shear formula Calculate, where is the height at which the mean wind component is measured, is the wind shear index.

3. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 2 is characterized in that: The sliding mode controller design in step S2 includes: Construct an error model based on the mathematical model of the UAV position control; Terminal sliding mode function ,in , For the design parameters, , They are Position tracking error and velocity tracking error on the axis, The design can improve the convergence speed of sliding variables. ensure Tracking error ; By controlling the amount, the accessibility of the sliding surface is ensured.

4. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 3 is characterized in that: The disturbance observer in step S3 is designed as: ， in, are the auxiliary variables bypassing that observer, is the observation gain used to adjust the observation speed of the observer, For drones The output of the controller on the axis, is the drag coefficient of the drone, For no one The speed of the axis, For drones The wind disturbance force on the shaft is For drones The expected acceleration on the axis, for Velocity tracking error on the axis, is the perturbation observation result.

5. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 4 is characterized in that: The wind energy utilization judgment conditions in step S4 include: Wind field disturbance utilization conditions ; Residual disturbance utilization conditions ; When the disturbance characteristics satisfy or When the disturbance is judged to be beneficial to the stability of the system, the utilization condition is set to =0 or =0, retain the corresponding disturbance to assist flight.

6. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 5 is characterized in that: The dynamic adjustment of the control strategy is achieved by updating the control quantity: ； in, It’s the quality of the drone. is the sliding mode function design parameter, is the upper bound of the remaining unknown disturbance About The symbol function of It is to take a value according to the judgment condition of step S4.

7. The energy-saving and wind-disturbance-resistant flight control method for unmanned aerial vehicles based on wind energy utilization according to claim 6 is characterized in that: When the energy-saving flight is realized by utilizing the disturbance in the operating environment in step S4, the effectiveness of the energy-saving flight needs to be further judged through the following steps: Select the Lyapunov function as , combined with the sliding mode function and control algorithms right The derivative is: ； in is the upper bound of the remaining unknown disturbance, It is the wind disturbance power. is the observed value of the disturbance To take a value according to the judgment condition of step S4; When the disturbance characteristics meet the utilization conditions, and Take 0 to retain the influence of disturbance, thereby improving The speed tends to 0 to achieve energy-saving and anti-interference flight.

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